With the development of the fingerprint detection and identification technology, the fingerprint identification technology has been applied more and more in the all kinds of fields. For example, the fingerprint identification technology is used in the fingerprint unlock function for mobile phones, computers and other mobile terminals. Among a large number of fingerprint detection and identification methods, the chip-based capacitive detection and identification method, because of its advantages such as small size, low power consumption, etc., becomes among first choices in the mobile phone and tablet market.
Nowadays, most of the fingerprint identification methods are based on characteristic-point algorithms, in which the characteristic points refer to the fork point and the end point in the ridge line of the fingerprint. When collecting finger prints, a larger size fingerprint detection chip can collect a larger fingerprint image area, and the characteristic points in the collected fingerprint image are relatively more; but a smaller size fingerprint detection chip can only collect the fingerprint image containing a relatively small number of characteristic points. When the fingerprint image contains fewer characteristic points, there is a certain difficulty to make the fingerprint identification. However, to many situations, it is necessary to process the fingerprint identification using the fingerprint image having fewer characteristic points. For example, due to the limit by the size and the thickness of the mobile terminal, the size of the fingerprint detection chip becomes smaller and smaller, and the thickness of the fingerprint detection chip becomes smaller and smaller, and thus the detected characteristic points of the fingerprint image are less. In addition, the fingerprint characteristic points of some people are very few and, even if the collection area is large enough, it is difficult to detect a lot of characteristic points.
In these conditions, because the characteristic point information is too little, it is easy to cause matching failure, and thus the collected fingerprint cannot be identified; or the matching is success but with the wrong identification result. Thus, the fingerprint identification success rate is low and the accuracy is poor.